Talk to any digital marketing or tech person about their field and chances are it won’t take too long before the words “big data” come up. It’s become such a megatrend that massive amounts of resources are being allocated by a growing number companies to the collection of data, virtually wherever it can be found.
And it is everywhere. Companies are collecting data on everything from their customers, and their consumption behavior — and from sources like point of sale, online surveys, retail outlets, and social media, among a plethora of other data streams.
This has resulted in a collection of data on a global level, the scale of which is virtually inconceivable — and something that is still growing.
So why are the business and tech worlds so enamored by big data? Why are such significant resources set aside for this purpose?
In the simplest of terms, some of the benefits of having big data includes:
Companies with ample resources have been quick to jump on the big data bandwagon because of its potential to provide with them with an advantage in this hyper-competitive world.
But, while the potential benefits are real, so are the challenges in actually making the data collected translate into insights that will lead to bigger revenues. And though industry practitioners and analysts are in agreement that those looking to get a leg up on the competition need to get into big data — they also agree that absent expert data analysis, it matters not how massive the amount of data you’re able to collect if you’re not versed on what to exactly do with it.
As Geoffrey Moore, author of digital marketing book, Crossing the Chasm, writes, “Without Big Data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”
Despite the prevalence of big data, and the continually growing number of companies integrating it into their operational practice, a vast number of them still don’t have a good enough grasp of how to turn the large amounts of data into quantifiable business profits.
As pointed out by Entrepreneur, Walmart — which has one of the biggest databases created, and who likely spend billions per year on big data — has yet to see an increase in revenues in spite of the resources spent on trying to get valuable insights from big data.
Similarly, Best Buy has spent a lot of money on big data, yet due to certain factors like its website (which has been described as “clunky”), has done even worse by seeing revenue that is declining.
Emerging technologies have made it increasingly easier to collect data from various streams; while services like data consolidation platform Querona, promise to make the endeavor even more convenient — by placing data from different sources accessible from one place.
But before you can begin to discover how big data can work for your business, you must first understand its source.
As noted by analytics leader SAS, this category includes data collected from a company’s IT system and its web of connected devices. Once this kind of data arrives, companies can decide what to keep and let go off, and what should be analyzed further.
Marketing, sales, and support functions benefit the most from this kind of data, which is mainly based on social interactions. But because this data often lacks structure, it presents quite a challenge in how it should be consumed and analyzed.
Essentially, these are data available through open sources like the US’ data.gov, the EU Open Data Portal, and the CIA World Factbook.
With a bevy of low-cost options, storing large amounts of data is no longer the challenge it was years ago.
Some experts believe that less is more when it comes to data analysis. They say it doesn’t matter if you collect less data as long as you collect relevant data.
A common mistake is focusing too much on the collection of as much data as possible, without have a concrete strategy of which to analyze, and how. With a solid analytics strategy in place, you put yourself in a position to determine upfront which data is relevant before analyzing it — saving you valuable time and resources.
Similarly, a sound strategy positions you to make informed business decisions confidently. When done correctly, big data analysis should lead to an abundance of valuable information, what you do with it is what determines your company’s success.
Everyone claims to have the solution — analytics and software companies promise to make your marketing efforts more informed and efficient under the guise of “expertise.”
But you can begin to sift through the sea of options, and separate the real contenders from the pretenders by taking the following into consideration:
Piortr Czarnas of Querona says that it is ideal to be able to have a big data service that provides access to all collected data in a lean way — which means having all data sources connected directly and available for analytics instantly.
He also notes that the ideal product should not only provide you access to data, but also have data modeling — the process used to define and analyze data requirements needed to support business processes, which are aligned with respective information systems.
Essentially, this means close coordination with data modelers and company stakeholders.
Almost every discussion about the application of big data eventually ends up with emphasis being placed on being able to identify relevant data, and having competent data scientists to analyze such data.
Everyone wants to get a competitive edge, but similar to other digital marketing trends, before you jump on the newest shiny toy, you must put careful thought on your company’s capability to effectively implement the new technology. Otherwise, valuable resources will ultimately end up being wasted.
Watch our episode of #AMWeekly where we talk with Piotr Czarnas, QUERONA, about how BI & Big Data analytics can help solve data-driven business problems here: